PSCL and GHG Reporting: How to Design a Survey That Meets Both Standards

In 2024, we analyzed over 200 PSCLs from Italian companies. One finding stands out: an increasing number of organizations find themselves having to prepare dual reporting:

the PSCL according to Ministerial Guidelines;
Scope 3 emission reporting according to the GHG Protocol.

The complexity lies not so much in data collection, but in their correct classification and in the application of appropriate emission factors.

In this article, we’ll unravel the complexity of this dual reporting and show how a well-designed survey can satisfy both standards with a single data collection, using GHG Protocol frameworks and appropriate emission factors.

The GHG Protocol Framework: Established Methodology for Commuting Emission Calculation

The GHG Protocol represents the most recognized international standard for corporate emission accounting. For Scope 3 Category 7 (Employee Commuting), the protocol provides three hierarchical calculation methodologies:

Fuel-based method: the most precise, requires actual employee fuel consumption data. In practice, it’s almost never applicable as consumption data for systematic home-work commuting is impossible to obtain.
Distance-based method: the most used, combines data on distances traveled and transportation modes with specific emission factors. The basic formula provides: CO2e emissions = Σ (annual total distance by mode × specific emission factor). Annual distances are calculated as: typical commute distance × 2 × days when home-work commute is made.
Average-data method: based on national averages, used when primary data is not available. Requires only the number of employees and applies average mobility patterns derived from national statistics.

The distance-based methodology represents the right balance between accuracy and operational feasibility, requiring information that a well-structured survey can effectively collect.

The Challenge of Emission Factors: Between National Standards and International References

The selection and application of emission factors often constitutes the most complex and delicate phase in emission reporting. Each database uses different calculation methodologies, variable perimeters, and updates with non-uniform timelines.

In Italy, the main reference remains ISPRA’s national emission inventory, accessible through the National Environmental Information System. ISPRA factors have the advantage of being calibrated on the national vehicle fleet and Italian mobility conditions. However, data granularity does not always meet international reporting needs.

For this reason, many Italian organizations integrate or replace national factors with international databases. Banca d’Italia, in its 2024 Management and Sustainability Report, documents the use of European and international databases to ensure comparability and reporting completeness.

DESNZ: The Evolution of DEFRA Factors and the New European Reference

Among international databases, DESNZ factors represent a de facto standard for European reporting. The Department for Energy Security and Net Zero, established in February 2023, inherited from DEFRA the responsibility to publish and update greenhouse gas conversion factors. This transition involved not only an organizational change but also a significant improvement in data structure and completeness.

DESNZ 2025 factors organize home-work transportation emissions into six main categories, clearly distinguishing between Scope 1, 2, and 3. This classification is particularly useful for companies that must report according to the GHG Protocol, as it eliminates ambiguity in emission allocation.

The modular structure of DESNZ factors also allows separate calculation of direct emissions (tank-to-wheel) from upstream emissions (well-to-tank), an increasingly required feature in advanced sustainability standards.

Operational Survey Structure: Mapping Between PSCL Requirements and DESNZ Categories

To capture all necessary data in a single collection, the survey must be structured according to this detailed matrix:

Required Information	Example Response Options	DESNZ Categories	GHG Scope
Weekly working days	4, 5, 6, variable	Homeworking	3
Days working from home	0, 1, 2, 3, 4, 5 days/week	Homeworking	3
Primary transportation mode	Car, motorcycle, public transport, bike, walking, mixed	All categories	1/2/3
Vehicle ownership	Company, private, company rental, car sharing	Passenger vehicles (S1) / Business travel-land (S3)	1 or 3
Fuel type	Gasoline, diesel, LPG, natural gas, hybrid, electric, PHEV	Passenger vehicles / WTT / UK electricity	1/2/3
Vehicle size	Small (<1.4L), Medium (1.4-2.0L), Large (>2.0L)	Passenger vehicles / Business travel-land	1 or 3
% electric mode (PHEV)	0-100%	UK electricity for EVs / Passenger vehicles	2 or 3
Average passengers (carpooling)	1, 2, 3, 4, 5+	All vehicle categories	-
Annual km traveled	Number	All transport categories	-
Public transport type	Bus, metro, tram, regional train, high-speed	Business travel-land	3
Charging location (EV)	Home, office, public, mixed	UK electricity for EVs	2 or 3

This detailed structure, while calibrated on DESNZ factors, maintains full compatibility with other emission databases. Collected data can be easily mapped to ISPRA, EEA, or other national standard factors, ensuring the flexibility needed to adapt to different reporting frameworks.

Three Critical Elements for Calculation Accuracy

1. The Distinction Between Company and Private Vehicles

The survey must precisely identify vehicle ownership. A company car generates Scope 1 emissions (if fuel-powered) or Scope 2 (if electric), while the same privately-owned vehicle generates Scope 3 emissions. This distinction, absent in the traditional PSCL framework, requires explicit questions and granular response options, including hybrid forms such as company long-term rental.

2. Well-to-Tank Emission Calculation

Upstream emissions can represent even 20-25% of total road transport emissions. These emissions, always allocated to Scope 3, are not contemplated in PSCL and must be calculated for both company and private vehicles, following the GHG Protocol completeness principle.

3. Remote Work Quantification

Remote work days are not simply the inverse of commuting days. Between vacation, training, business trips, and various absences, the total rarely corresponds to theoretical working days. The survey must therefore explicitly ask for both presence days and remote work days, allowing calculation of additional domestic emissions according to DESNZ methodology for homeworking.

4. The Importance of Public Transport Type

While not strictly necessary for PSCL, distinguishing the type of public transport used is crucial for accurate emission analysis. Different public transport means, such as buses, trains, or subways, have different emission factors. Therefore, the survey should include specific questions to identify the type of public transport used, thus improving the precision of overall emission calculation.

Statistical Representativeness: Minimum Thresholds per Location

The representativeness of emission calculations loses value without adequate survey participation. Statistical analysis, based on a 95% confidence level and ±5% margin of error, indicates differentiated minimum thresholds:

Locations up to 100 employees: 80% participation required
Locations with 200 employees: 66% response sufficient
Locations with 500 employees: 43% participation adequate
Locations over 1,000 employees: 28% ensures representativeness

In other words: the smaller the location, the greater the participation must be to guarantee emission calculation representativeness.

It’s important to emphasize that these values apply per individual location, not for the corporate aggregate. A multi-site organization must reach minimum thresholds at each location, as mobility patterns vary significantly between territories. Milan and Bari present profoundly different transportation options, average distances, and commuting habits.

Practical Implementation: From Theory to Action

The transition to a dual-standard survey requires three sequential interventions:

First, updating the survey with questions necessary for Scope classification and WTT calculation;
Then, configuring the calculation system to apply selected emission factors, whether ISPRA, DESNZ, or others;
Finally, validating results through comparisons with sector benchmarks and internal consistency analysis.

The initial investment in this structuring is quickly repaid. A single survey generates data for PSCL, GHG reporting, sustainability certifications, and predictive analysis. Mobility Managers who implement this approach now transform a regulatory requirement into a strategic management tool that’s cross-functional throughout the organization.

The convergence between PSCL and GHG reporting represents not only a regulatory requirement, but a value opportunity for organizations. Implementing a dual-standard survey allows companies to:

Eliminate duplication of processes and communications, optimizing operational efficiency
Improve data quality through higher participation rates and more targeted collection
Enhance the role of mobility managers, transforming them into strategic partners of sustainability teams
Enable deeper analyses on systematic mobility, thanks to the granularity of collected data
Design more effective home-work mobility measures, based on concrete and comparable evidence